How to Calculate Statistical Mode in R

March 15, 2026 · 2 min read ·Updated May 28, 2026 ·beginner

rstatisticsmodevectorsdplyr

Calculate statistical mode to find the most frequent value in a vector. R has no built-in function for this — mode() returns the storage type of an object, not the most frequent value — so you need a short custom function that counts unique values and picks the one with the highest count. This recipe covers both a simple approach that returns the first mode and a tie-aware version that returns all modes when multiple values share the top frequency. The same pattern works on data frame columns by wrapping the logic inside dplyr::summarise().

get_mode <- function(x) {
  x <- x[!is.na(x)]
  ux <- unique(x)
  ux[which.max(tabulate(match(x, ux)))]
}

x <- c(1, 2, 2, 3, 3, 3, 4, NA)
get_mode(x)
# [1] 3

This function strips NA values, finds the unique elements, then counts how often each appears with tabulate(). The which.max() call returns only the first mode — if there is a tie, you lose the other winning values.

For data frames, dplyr::count() with slice_head() does the same job in one pipeline:

library(dplyr)

df <- data.frame(color = c("red", "blue", "blue", "green", "green", "green"))
df %>% count(color, sort = TRUE) %>% slice_head(n = 1)

To return all modes when multiple values tie for the highest frequency, replace which.max() with equality against the max count:

get_mode <- function(x) {
  x <- x[!is.na(x)]
  ux <- unique(x)
  tab <- tabulate(match(x, ux))
  ux[tab == max(tab)]
}

See also